Taming Multiple Binding Poses in Alchemical Binding Free Energy Prediction: the $\beta$-cyclodextrin Host-Guest SAMPL9 Blinded Challenge

TL;DR

This study applies the Alchemical Transfer Method with a custom force field to predict binding free energies in complex host-guest systems, addressing multiple binding poses and conformational challenges, with results closely matching experimental data.

Contribution

It demonstrates the effectiveness of ATM and enhanced sampling techniques in predicting binding free energies for complex cyclodextrin host-guest systems in a blinded challenge.

Findings

Predicted binding affinities closely match experimental data.

Metadynamics sampling improves convergence of free energy estimates.

Challenges include conformational trapping and multiple binding poses.

Abstract

We apply the Alchemical Transfer Method (ATM) and a bespoke fixed partial charge force field to the SAMPL9 bCD host-guest binding free energy prediction challenge that comprises a combination of complexes formed between five phenothiazine guests and two cyclodextrin hosts. Multiple chemical forms, competing binding poses, and computational modeling challenges pose significant obstacles to obtaining reliable computational predictions for these systems. The phenothiazine guests exist in solution as racemic mixtures of enantiomers related by nitrogen inversions that bind the hosts in various binding poses, each requiring an individual free energy analysis. Due to the large size of the guests and the conformational reorganization of the hosts, which prevent a direct absolute binding free energy route, binding free energies are obtained by a series of absolute and relative binding alchemical steps for each chemical species in each binding pose. Metadynamics-accelerated conformational sampling was found to be necessary to address the poor convergence of some numerical estimates affected by conformational trapping. Despite these challenges, our blinded predictions quantitatively reproduced the experimental affinities for the $\beta$-cyclodextrin host, less one case of the methylated derivative being an outlier. The work illustrates the challenges of obtaining reliable free energy data in in-silico drug design for even seemingly simple systems and introduces some of the technologies available to tackle them.